Refer to the exhibit.

Click on the calculator icon in the upper left corner. An analyst is searching a corpus of documents for the topic “solid state disk”. In the Exhibit, Table A provides the inverse document frequency for each term across the corpus. Table B provides each term’s frequency in four documents selected from corpus. Which of the four documents is most relevant to the analyst’s search?

Refer to the exhibit.

Which type of data issue would you suspect based on the exhibit?

Refer to the exhibit.

In the exhibit, a correlogram is provided based on an autocorrelation analysis of a sample dataset.
What can you conclude from only this exhibit?

Refer to the exhibit

Consider the training data set shown in the exhibit. What are the classification (Y = 0 or 1) and the probability of the classification for the tupleX(0, 0, 1) using Naive Bayesian classifier?

Refer to the exhibit.

You are using k-means clustering to discover groupings within a data set. You plot within-sum-of-squares (wss) of multiple cluster sizes. Based on the exhibit, how many clusters should you use in your analysis?

Refer to the exhibit.

Click on the calculator icon in the upper left corner. You are given a list of pre-defined association rules:
A) RENTER => BAD CREDIT
B) RENTER => GOOD CREDIT
C) HOME OWNER => BAD CREDIT
D) HOME OWNER => GOOD CREDIT
E) FREE HOUSING => BAD CREDIT
F) FREE HOUSING => GOOD CREDIT
For your next analysis, you must limit your dataset based on rules with confidence greater than 60%.
Which of the rules will be kept in the analysis?

Refer to the exhibit.

You are using K-means clustering to classify customer behavior for a large retailer. You need to determine the optimum number of customer groups. You plot the within-sum-of-squares (wss) data as shown in the exhibit. How many customer groups should you specify?

Refer to the exhibit.

You have run a linear regression model against your data, and have plotted true outcome versus predicted outcome. The R-squared of your model is 0.75. What is your assessment of the model?

Refer to the exhibit.

After analyzing a dataset, you report findings to your team:
1. Variables A and C are significantly and positively impacting the dependent variable.
2. Variable B is significantly and negatively impacting the dependent variable.
3. Variable D is not significantly impacting the dependent variable.
After seeing your findings, the majority of your team agreed that variable B should be positively
impacting the dependent variable.
What is a possible reason the coefficient for variable B was negative and not positive?

Refer to the Exhibit.

You are working on creating an OLAP query that outputs several rows of with summary rows of subtotals and grand totals in addition to regular rows that may contain NULL as shown in the exhibit. Which function can you use in your query to distinguish the row from a regular row to a subtotal row?